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Items: 36

1.

Error-correcting dynamics in visual working memory.

Panichello MF, DePasquale B, Pillow JW, Buschman TJ.

Nat Commun. 2019 Jul 29;10(1):3366. doi: 10.1038/s41467-019-11298-3.

2.

Model-based targeted dimensionality reduction for neuronal population data.

Aoi MC, Pillow JW.

Adv Neural Inf Process Syst. 2018 Dec;31:6690-6699.

3.

Efficient inference for time-varying behavior during learning.

Roy NA, Bak JH, Akrami A, Brody CD, Pillow JW.

Adv Neural Inf Process Syst. 2018 Dec;31:5695-5705.

4.

Scaling the Poisson GLM to massive neural datasets through polynomial approximations.

Zoltowski DM, Pillow JW.

Adv Neural Inf Process Syst. 2018 Dec;31:3517-3527.

5.

Discrete Stepping and Nonlinear Ramping Dynamics Underlie Spiking Responses of LIP Neurons during Decision-Making.

Zoltowski DM, Latimer KW, Yates JL, Huk AC, Pillow JW.

Neuron. 2019 Jun 19;102(6):1249-1258.e10. doi: 10.1016/j.neuron.2019.04.031. Epub 2019 May 23.

PMID:
31130330
6.

Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias.

Cai MB, Schuck NW, Pillow JW, Niv Y.

PLoS Comput Biol. 2019 May 24;15(5):e1006299. doi: 10.1371/journal.pcbi.1006299. eCollection 2019 May.

7.

Adaptive stimulus selection for multi-alternative psychometric functions with lapses.

Bak JH, Pillow JW.

J Vis. 2018 Nov 1;18(12):4. doi: 10.1167/18.12.4.

8.

Lawful tracking of visual motion in humans, macaques, and marmosets in a naturalistic, continuous, and untrained behavioral context.

Knöll J, Pillow JW, Huk AC.

Proc Natl Acad Sci U S A. 2018 Oct 30;115(44):E10486-E10494. doi: 10.1073/pnas.1807192115. Epub 2018 Oct 15.

9.

Systematic misperceptions of 3-D motion explained by Bayesian inference.

Rokers B, Fulvio JM, Pillow JW, Cooper EA.

J Vis. 2018 Mar 1;18(3):23. doi: 10.1167/18.3.23.

10.

Dethroning the Fano Factor: A Flexible, Model-Based Approach to Partitioning Neural Variability.

Charles AS, Park M, Weller JP, Horwitz GD, Pillow JW.

Neural Comput. 2018 Apr;30(4):1012-1045. doi: 10.1162/neco_a_01062. Epub 2018 Jan 30.

11.

Combined Social and Spatial Coding in a Descending Projection from the Prefrontal Cortex.

Murugan M, Jang HJ, Park M, Miller EM, Cox J, Taliaferro JP, Parker NF, Bhave V, Hur H, Liang Y, Nectow AR, Pillow JW, Witten IB.

Cell. 2017 Dec 14;171(7):1663-1677.e16. doi: 10.1016/j.cell.2017.11.002. Epub 2017 Dec 7.

12.

Gaussian process based nonlinear latent structure discovery in multivariate spike train data.

Wu A, Roy NA, Keeley S, Pillow JW.

Adv Neural Inf Process Syst. 2017 Dec;30:3496-3505.

13.

Capturing the Dynamical Repertoire of Single Neurons with Generalized Linear Models.

Weber AI, Pillow JW.

Neural Comput. 2017 Dec;29(12):3260-3289. doi: 10.1162/neco_a_01021. Epub 2017 Sep 28.

PMID:
28957020
14.

Is population activity more than the sum of its parts?

Pillow JW, Aoi MC.

Nat Neurosci. 2017 Aug 29;20(9):1196-1198. doi: 10.1038/nn.4627. No abstract available.

PMID:
28849790
15.

Discovering Event Structure in Continuous Narrative Perception and Memory.

Baldassano C, Chen J, Zadbood A, Pillow JW, Hasson U, Norman KA.

Neuron. 2017 Aug 2;95(3):709-721.e5. doi: 10.1016/j.neuron.2017.06.041.

16.

Functional dissection of signal and noise in MT and LIP during decision-making.

Yates JL, Park IM, Katz LN, Pillow JW, Huk AC.

Nat Neurosci. 2017 Sep;20(9):1285-1292. doi: 10.1038/nn.4611. Epub 2017 Jul 24.

17.

Volumetric two-photon imaging of neurons using stereoscopy (vTwINS).

Song A, Charles AS, Koay SA, Gauthier JL, Thiberge SY, Pillow JW, Tank DW.

Nat Methods. 2017 Apr;14(4):420-426. doi: 10.1038/nmeth.4226. Epub 2017 Mar 20.

18.

Dissociated functional significance of decision-related activity in the primate dorsal stream.

Katz LN, Yates JL, Pillow JW, Huk AC.

Nature. 2016 Jul 14;535(7611):285-8. doi: 10.1038/nature18617. Epub 2016 Jul 4.

19.

Response to Comment on "Single-trial spike trains in parietal cortex reveal discrete steps during decision-making".

Latimer KW, Yates JL, Meister ML, Huk AC, Pillow JW.

Science. 2016 Mar 25;351(6280):1406. doi: 10.1126/science.aad3596.

20.

Explaining the especially pink elephant.

Pillow JW.

Nat Neurosci. 2015 Oct;18(10):1435-6. doi: 10.1038/nn.4122. No abstract available.

PMID:
26404720
21.

NEURONAL MODELING. Single-trial spike trains in parietal cortex reveal discrete steps during decision-making.

Latimer KW, Yates JL, Meister ML, Huk AC, Pillow JW.

Science. 2015 Jul 10;349(6244):184-7. doi: 10.1126/science.aaa4056.

22.

The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction.

Williamson RS, Sahani M, Pillow JW.

PLoS Comput Biol. 2015 Apr 1;11(4):e1004141. doi: 10.1371/journal.pcbi.1004141. eCollection 2015 Apr. Erratum in: PLoS Comput Biol. 2019 Jun 14;15(6):e1007139.

23.

Encoding and decoding in parietal cortex during sensorimotor decision-making.

Park IM, Meister ML, Huk AC, Pillow JW.

Nat Neurosci. 2014 Oct;17(10):1395-403. doi: 10.1038/nn.3800. Epub 2014 Aug 31.

24.

Bayesian active learning of neural firing rate maps with transformed gaussian process priors.

Park M, Weller JP, Horwitz GD, Pillow JW.

Neural Comput. 2014 Aug;26(8):1519-41. doi: 10.1162/NECO_a_00615. Epub 2014 May 30.

PMID:
24877730
25.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

Pillow JW, Shlens J, Chichilnisky EJ, Simoncelli EP.

PLoS One. 2013 May 3;8(5):e62123. doi: 10.1371/journal.pone.0062123. Print 2013.

26.

The 8th annual computational and systems neuroscience (Cosyne) meeting.

Histed MH, Pillow JW.

Neural Syst Circuits. 2011 Apr 20;1(1):8. doi: 10.1186/2042-1001-1-8. No abstract available.

27.

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells.

Vidne M, Ahmadian Y, Shlens J, Pillow JW, Kulkarni J, Litke AM, Chichilnisky EJ, Simoncelli E, Paninski L.

J Comput Neurosci. 2012 Aug;33(1):97-121. doi: 10.1007/s10827-011-0376-2. Epub 2011 Dec 29.

28.

Receptive field inference with localized priors.

Park M, Pillow JW.

PLoS Comput Biol. 2011 Oct;7(10):e1002219. doi: 10.1371/journal.pcbi.1002219. Epub 2011 Oct 27.

29.

Efficient Markov chain Monte Carlo methods for decoding neural spike trains.

Ahmadian Y, Pillow JW, Paninski L.

Neural Comput. 2011 Jan;23(1):46-96. doi: 10.1162/NECO_a_00059. Epub 2010 Oct 21.

30.

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

Pillow JW, Ahmadian Y, Paninski L.

Neural Comput. 2011 Jan;23(1):1-45. doi: 10.1162/NECO_a_00058. Epub 2010 Oct 21.

PMID:
20964538
31.

Heterogeneous response dynamics in retinal ganglion cells: the interplay of predictive coding and adaptation.

Nirenberg S, Bomash I, Pillow JW, Victor JD.

J Neurophysiol. 2010 Jun;103(6):3184-94. doi: 10.1152/jn.00878.2009. Epub 2010 Mar 31.

32.

Spatio-temporal correlations and visual signalling in a complete neuronal population.

Pillow JW, Shlens J, Paninski L, Sher A, Litke AM, Chichilnisky EJ, Simoncelli EP.

Nature. 2008 Aug 21;454(7207):995-9. doi: 10.1038/nature07140. Epub 2008 Jul 23.

33.

Spike-triggered neural characterization.

Schwartz O, Pillow JW, Rust NC, Simoncelli EP.

J Vis. 2006 Jul 17;6(4):484-507.

PMID:
16889482
35.

Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model.

Pillow JW, Paninski L, Uzzell VJ, Simoncelli EP, Chichilnisky EJ.

J Neurosci. 2005 Nov 23;25(47):11003-13.

36.

Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model.

Paninski L, Pillow JW, Simoncelli EP.

Neural Comput. 2004 Dec;16(12):2533-61.

PMID:
15516273

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